Effects of noise correlation on least squares filtering in multipath detection for GNSS

S. Ugazio, L. Presti
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引用次数: 3

Abstract

In GNSS (Global Navigation Satellite System) multipath (MP) results to be one of the main error sources affecting the GNSS solution. In this paper a Linear Adaptive Filter (LAF) technique [1] is applied, based on Least Squares (LS), to estimate the MP coefficients and delay by using a post-correlation approach. An assumption using LAFs [1] is the noise to be a white process, but considering post-correlation data the hypothesis of uncorrelation among the samples is not valid. The LAF is a stat-of-the-art technique, but not in the GNSS-MP-detection and mitigation field. With the objective of using this method for this purpose, the effects of the noise correlation in LS filters are studied in this paper, when the technique is applied to GNSS channel estimate in post-correlation. In this paper, a preliminary analysis is done, by means of simulations. Comparisons are shown between data affected by correlated and uncorrelated noise, using realistic GNSS data.
GNSS多径检测中噪声相关性对最小二乘滤波的影响
在全球卫星导航系统(GNSS)中,多路径(MP)结果是影响GNSS解决方案的主要误差源之一。本文采用基于最小二乘(LS)的线性自适应滤波(LAF)技术[1],通过后相关方法估计MP系数和延迟。使用LAFs[1]的假设是噪声是白过程,但考虑到后相关数据,样本间不相关的假设是不成立的。LAF是最先进的技术,但不是在gnss - mp探测和减缓领域。为了实现这一目标,本文研究了LS滤波器中噪声相关对后相关GNSS信道估计的影响。本文通过仿真对其进行了初步分析。使用实际GNSS数据对受相关和不相关噪声影响的数据进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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